The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto–optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. ...

This paper presents a differential evolution algorithm to solve the permutaion flowshop sequencing problem with makespan criterion. Differential evolution is one of the latest evolutionary optmization algorithm applied to continuous optimization problems where members of population use chromosomes based on floating-point numbers to represent candidate solutions. In this paper we also present a ...

This paper develops a bi-directional prediction approach to predict the production parameters and performance of differential fibers based on neural networks and a multi-objective evolutionary algorithm. The proposed method does not require accurate description and calculation for the multiple processes, different modes and complex conditions of fiber production. The bi-directional prediction a...

Evolutionary Algorithms (EAs) are stochastic and robust meta-heuristics of evolutionary computation field useful to solve optimization problems in image processing applications. Recently, as special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used in various designs of EAs. Three differential evolution approaches based on chaotic sequ...

with the rapid development of the internet, the amount of information and data which are produced, are extremely massive. hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. data mining can overcome this problem. while data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. as the speed of ...

optimal design of cantilever reinforced concrete retaining wall can lead considerable cost saving if its involvement in hill road formation and railway line formation is significant.  a study of weight reduction optimization of reinforced cantilever retaining wall subjected to a sloped backfill using differential evolution algorithm (dea) is carried out in the present research.  the retaining w...

Economic Load Dispatch (ELD) is an important and difficult optimization problem in power system planning. This article aims at addressing two practically important issues related to ELD optimization: (1) analyzing the ELD problem from the perspective of evolutionary optimization; (2) developing effective algorithms for ELD problems of large scale. The first issue is addressed by investigating t...

Differential Evolution algorithm is a simple yet reliable and robust evolutionary algorithm for numeric optimization. However, fine-tuning control parameters of DE algorithm is a tedious and time-consuming task thus became a major challenge for its application. This paper introduces a novel self-adaptive method for tuning the amplification parameters F of DE dynamically. This method sampled app...

Broadcasting antenna array null filling is a very challenging problem for antenna design optimization. This paper compares five antenna design optimization algorithms (Differential Evolution, Particle Swarm, Taguchi, Invasive Weed, Adaptive Invasive Weed) as solutions to the antenna array null filling problem. The algorithms compared are evolutionary algorithms which use mechanisms inspired by ...